ENGAGE研究:评估一个对话式虚拟代理,为癌症患者提供量身定制的测试前遗传教育
Kala Visvanathan1, Dana Petry2, Michelle S McCullough3
1Johns Hopkins School of Medicine and Bloomberg School of Public Health, #E6142 615 N. Wolfe Street, Baltimore, MD, 21231, USA. kvisvan1@jhu.edu.
Journal of cancer survivorship : research and practice
|December 8, 2023
概括
人工智能 (AI) 在测试之前为癌症患者提供了定制的基因教育,增强了知情决策. 这种人工智能工具被证明是安全的,用户友好和方便的患者,支持其进一步的评估.
科学领域:
- 在瘤学瘤学.
- 遗传学 遗传学 是一个
- 医疗信息学 医疗信息学
背景情况:
- 优质的遗传教育对于明智的癌症治疗决策至关重要.
- 需要新的方法来改善癌症患者获得基因教育的机会.
- 目前的方法往往缺乏可扩展性和患者的便利性.
研究的目的:
- 评估人工智能 (AI) 干预措施,为癌症患者提供遗传教育.
- 评估使用人工智能用于患者遗传教育的非遗传提供者的可行性.
- 通过可访问的基因测试前教育,使知情的治疗决策成为可能.
主要方法:
- 在HealthFAX平台上开发了一个对话式AI应用程序.
- 人工智能工具为正在接受积极治疗的癌症患者提供了定制的基因教育.
- 在约翰霍普金斯医院评估了患者的采用,使用和经验.
主要成果:
- 在64名同意的患者中,有51人访问了人工智能工具,在平均24分钟内在家中完成.
- 参与者报告该工具是安全的,易于使用,方便,并提供有价值的信息.
- 在接受测试结果之前,98%的参与者完成了遗传教育,其中16%确定了致病变体.
结论:
- 人工智能驱动的基因教育是癌症患者的可行和令人满意的方法.
- 人工智能应用程序展示了对患者的高可用性和方便性.
- 需要进一步的大规模研究来评估这种具有成本效益的人工智能干预.
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